An integrated indenter-ARFI imaging system for tissue stiffness quantification.
The goal of this work is to develop and characterize an integrated indenter-ARFI (acoustic radiation force impulse) imaging system. This system is capable of acquiring matched datasets of ARFI images and stiffness profiles from ex vivo tissue samples, which will facilitate correlation of ARFI images of tissue samples with independently-characterized material properties. For large and homogeneous samples, the indenter can be used to measure the Young's moduli by using Boussinesq's solution for a load on the surface ofa semi-infinite isotropic elastic medium. Experiments and finite element method (FEM) models were designed to determine the maximum indentation depth and minimum sample size for accurate modulus reconstruction using this solution. Applying these findings, indentation measurements were performed on three calibrated commercial tissue-mimicking phantoms and the results were in good agreement with the calibrated stiffness. For heterogeneous tissue samples, indentation can be used independently to characterize relative stiffness variation across the sample surface, which can then be used to validate the stiffness variation in registered ARFI images. Tests were performed on heterogeneous phantoms and freshly-excised colon cancer specimens to detect the relative stiffness and lesion sizes using the combined system. Normalized displacement curves across the lesion surface were calculated and compared. Good agreement ofthe lesion profiles was observed between indentation and ARFI imaging.
Zhai
Liang
L
Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA. liang.zhai@duke.edu
Palmeri
Mark L
ML
Bouchard
Richard R
RR
Nightingale
Roger W
RW
Nightingale
Kathryn R
KR
D003110:Colonic Neoplasms / Q000000981:diagnostic imaging*; D054459:Elasticity Imaging Techniques / Q000295:instrumentation*; D004867:Equipment Design; D020342:Finite Element Analysis; D006801:Humans; D066298:In Vitro Techniques; D019047:Phantoms, Imaging